1. Field
This application relates generally to the field of machine vision, and more specifically to a system and method for distributing a machine-vision analysis across multiple processors.
2. Description of Related Art
Machine vision is frequently used for product inspection in an industrial setting. In a typical machine-vision implementation, a digital image or video of a product is captured using a digital camera or optical sensor. By analyzing the digital image or video, key features of the product can be measured and the product can be inspected for defects.
In some industrial applications, machine vision is used to inspect parts on a production line. In order to keep up with production, the machine-vision processing rate should be at least as fast as the manufacturing production rate. However, in some cases, the machine-vision processing is computationally expensive and takes a significant amount of time to perform. As a result the machine-vision analysis cannot keep up with the rate of production. In this case, the production capacity may be limited by the machine-vision analysis, which is generally undesirable.
One solution to this problem is to increase the processing speed of the computer processor performing the machine-vision analysis. However, this approach may not be practical because faster processors are typically much more expensive. Additionally, there may be a diminishing return on the amount of processing speed that can be gained by purchasing faster, more expensive processors. This approach is also not necessarily scalable to address dynamically changing machine-vision processing loads or production rates.
Another solution is to limit the amount of machine-vision analysis that is performed by the processor to reduce the analysis time. However, this approach may not be practical or even possible in scenarios that require a detailed analysis of a high-resolution image to perform an inspection of the product.
The methods and systems described herein can be used to increase the processing capacity of a machine-vision system without the drawbacks of the approaches discussed above.